Guidelines to Study Differences in Expressiveness between Ontology Specification Languages: A Case Of Study

We focus on our experiences on translating ontologies between two ontology languages, FLogic and Ontolingua, in the framework of Methontology and ODE. Rather than building "ad hoc" translators between languages or using KIF, our option consists of translating through ODE intermediate representations. So, we have built direct translators from ODE intermediate representations to Ontolingua and FLogic, and we have also built reverse translators from these two languages to ODE intermediate representations. Expressiveness of the target languages is the main feature to analyse when automatically generating ontologies from ODE intermediate representations. Therefore, we analyse the expressiveness of Ontolingua and FLogic for creating classes, instances, relations, functions and axioms, which are the essential components in ontologies. The motivation for this analysis can be found in the (KA)² initiative and can be easily extended to any other domains and languages

How to Find Suitable Ontologies Using an Ontology-based WWW Broker

Knowledge reuse by means of outologies now faces three important problems: (1) there are no standardized identifying features that characterize ontologies from the user point of view; (2) there are no web sites using the same logical organization, presenting relevant information about ontologies; and (3) the search for appropriate ontologies is hard, time-consuming and usually fruitless. To solve the above problems, we present: (1) a living set of features that allow us to characterize ontologies from the user point of view and have the same logical organization; (2) a living domain ontology about ontologies (called ReferenceOntology) that gathers, describes and has links to existing ontologies; and (3) (ONTO)2Agent, the ontology-based www broker about ontologies that uses the Reference Ontology as a source of its knowledge and retrieves descriptions of ontologies that satisfy a given set of constraints. (ONTO)~Agent is available at http://delicias.dia.fi.upm.es/REFERENCE ONTOLOGY

Evaluating Knowledge Representation and Reasoning Capabilites of Ontology Specification Languages

The interchange of ontologies across the World Wide Web (WWW) and the cooperation among heterogeneous agents placed on it is the main reason for the development of a new set of ontology specification languages, based on new web standards such as XML or RDF. These languages (SHOE, XOL, RDF, OIL, etc) aim to represent the knowledge contained in an ontology in a simple and human-readable way, as well as allow for the interchange of ontologies across the web. In this paper, we establish a common framework to compare the expressiveness of "traditional" ontology languages (Ontolingua, OKBC, OCML, FLogic, LOOM) and "web-based" ontology languages. As a result of this study, we conclude that different needs in KR and reasoning may exist in the building of an ontology-based application, and these needs must be evaluated in order to choose the most suitable ontology language(s)

Towards a benchmark of the ODE API methods for accessing ontologies in the WebODE platform

Ontology editors and ontology engineering platforms allow creating and maintaining ontologies and using them in a wide range of applications, but there are neither specific benchmark for evaluating ontology platforms nor for evaluating their ontology access services. In this paper we present how we have designed and structured a benchmark for the ontology access services of the WebODE platform. We also present some results and analysis of the benchmark suite execution

Knowledge Base Reuse With Frame Representation In Artificial Intelligence Applications

The creation and upkeep of knowledge bases have emerged as the primary issue in artificial intelligence development. The knowledge domain is expanding, and application interoperability is urgently demanded. To accommodate this modification, the knowledge base, which serves as the foundation of the artificial intelligence architecture, must be updated. XML (extensible markup language), RDF (resources description framework), DAML (DARPA agent markup language), OIL (ontology inference layer), and OKBC are just a few of the standards that have been introduced as a result of the development of the internet (Open Knowledge-Base Connectivity). One type of knowledge representation that can store information and facts about a subject is frame-based representation. The OKBC, which can help with knowledge base interoperability, supports this approach. In this work, the main issues covered are the comprehension and fundamentals of knowledge base creation with frame representation. To better understand how frame representation functions as a reusable component, a case study from a news publication were used as an example

Overview of Knowledge Sharing and Reuse Components: Ontologies and Problem-Solving Methods

Ontologies and problem-solving methods are promising candidates for reuse in Knowledge Engineering. Ontologies define domain knowledge at a generic level, while problem-solving methods specify generic reasoning knowledge. Both type of components can be viewed as complementary entities that can be used to configure new knowledge systems from existing, reusable components. In this paper, we give an overview of approaches for ontologies and problem-solving methods

The integration of OntoClean in WebODE

Enterprises will only be interested in the use of ontologies if such ontologies are evaluated enough. Therefore, the development of ontology evaluation tools is a crucial matter. We have built the ODEClean module in the workbench for building ontologies named WebODE. ODEClean allows cleaning taxonomies following the OntoClean method, and WebODE provides technical support to the Methontology methodology for building ontologies. We approached the development of this module in two steps. Firstly, we have integrated the OntoClean method into the conceptualisation activity of Methontology. Secondly, we have designed and implemented ODEClean using a declarative approach for specifying the knowledge to be used on the evaluation. ODEClean uses: (a) the Top Level of Universals, (b) metaproperties based on philosophical notions, and (c) OntoClean evaluation axioms. The main advantage of this approach is that the system could easily allow the user relax or stress the evaluation of the taxonomy just selecting more or less meta-properties

A benchmark suite for evaluating the performance of the WebODE Ontology Engineering Platform

Ontology tools play a key role in the development and maintenance of the Semantic Web. Hence, we need in one hand to objectively evaluate these tools, in order to analyse whether they can deal with actual and future requirements, and in the other hand to develop benchmark suites for performing these evaluations. In this paper, we describe the method we have followed to design and implement a benchmark suite for evaluating the performance of the WebODE ontology engineering workbench, along with the conclusions obtained after using this benchmark suite for evaluating WebODE

WebODE: A Scalable Workbench for Ontological Engineering

This paper presents WebODE as a workbench for ontological engineering that not only allows the collaborative edition of ontologies at the knowledge level, but also provides a scalable architecture for the development of other ontology development tools and ontology-based applications. First, we will describe the knowledge model of WebODE, which has been mainly extracted and improved from the reference model of METHONTOLOGY’s intermediate representations. Later, we will present its architecture, together with the main functionalities of the WebODE ontology editor, such as its import/export service, translation services, ontology browser, inference engine and axiom generator, and some services that have been integrated in the workbench: WebPicker, OntoMerge and the OntoCatalogue